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Abstract

The potential to visualize and analyse geological outcrops in a 3D environment has
made terrestrial laser scanning (TLS) a standard method in geological field studies.
Lidar models can be integrated with high resolution photographs to generate photorealistic
3D models, also referred to as virtual outcrop models (VOMs) in geological
applications. However, the extraction of mineralogy and geochemical variations from
VOMs is limited to the visible light of the photographs and to the single spectral band
provided by the laser sensor. Imaging spectrometry applied from airborne and
spaceborne platforms is an established method for the regional mapping of
mineralogy and lithology, utilising the interaction of solar radiation with the Earth’s
surface. Many minerals and rocks can be mapped and analysed in a non-contact
manner by utilizing their diagnostic absorption properties within the visible and
particularly within the infrared spectral range.
The aim of this research is to apply imaging spectrometry with a ground-based
instrument to enable mineralogical and lithological analysis of near-vertical outcrop
sections. The terms ground-based and close-range are used to indicate a nearhorizontal
setup, as opposed to the nadir view found in airborne and spaceborne
applications. A workflow has been developed to integrate hyperspectral
classifications with 3D lidar models, to compliment VOMs with reliable information
about the mineralogy and geochemical variations in the outcrop. The workflow
includes data acquisition, spectral and photogrammetric processing of the
hyperspectral images, data integration and classifying VOMs utilising hyperspectral
image products. A newly developed hyperspectral imager designed as a compact and
lightweight instrument, and therefore practical for field applications, has been used.
The HySpex SWIR-320m sensor operates within the short wave infrared light
(SWIR) with a spectral range between 1.3-2.5 μm.
The spectral data were processed with methods primarily developed for airborne and
spaceborne applications. All images showed a significant amount of image artefacts,
mainly related to the irregular illumination-viewing geometry and bad pixels. While
image nonuniformities such as bad pixels are a common problem in pushbroom
scanning, other artefacts such as intensity gradients in along-track direction are
exacerbated by the close-range scanning and panoramic image geometry. Applying
different nonuniformity corrections, image artefacts were minimized but could not be
completely removed. For materials with 50% reflectance a signal to noise ratio better
than 70:1 was achieved. Atmospheric corrections were performed utilising an
Empirical Line correction, based on two reference spectra measured from calibrated Spectralon panels which were placed in the image scene. Due to a restricted view of
the upper hemisphere in close-range scanning, the obtained reflectance values need to
be considered as conic-directional reflectance. To separate and remove image noise
Maximum Noise Fraction transform was applied. Spectral classification and mapping
was performed using different approaches including band ratios, Spectral Angle
Mapping, Spectral Feature Fitting and Mixture Tuned Match Filtering. Based on a
cylindrical camera model, VOMs could be integrated and textured with hyperspectral
image products with an accuracy of one image pixel.
Two case studies from different geological settings were carried out, to demonstrate
how close-range hyperspectral imaging can help improve the analysis of vertical
outcrops. In the Pozalagua quarry (Spain), hydrothermal dolomitized limestone of
Cretaceous platform-slope carbonates have been spectrally mapped. Despite very
similar chemical and spectral properties, different dolomite and limestone types, as
well as calcite could be distinguished and mapped in the outcrop. Spectral differences
of two main dolomite types could be related to different manganese and iron contents,
as confirmed by chemical analysis. Although detailed spectral analysis was disturbed
by surface weathering products, dolomite and limestone were also mapped on
weathered surfaces. A limestone unit initially missed by conventional field
observations, due to similar visual appearance compared to the surrounding
carbonates, was clearly identified and mapped by spectral means. The second field
area was Garley canyon (Utah, USA), where a shallow marine, shoreface succession
was studied. Carbonate and clay abundances were determined to map and quantify
carbonate concretions, and to map siltstone and sandstone in the outcrop. Carbonate
concretions have implications for reducing porosity and permeability in shallow
marine sandstones.
Results show that close-range imaging spectrometry can provide reliable qualitative
and quantitative information about the mineral-chemical composition of exposed
surfaces. Further research is required to improve the nonuniformity, atmospheric and
topographic correction of the spectral images and to adjust the processing to the
close-range scanning and image geometry. However, the method can be adapted to
other applications in which the collection and analysis of chemical surface
composition and geometric information is required, such as in mining, building
damage assessment or in forestry for canopy analysis. With an increased availability
of lightweight hyperspectral imagers it is expected that close-range imaging
spectrometry will become a sub-discipline in remote sensing, and a standard method
in field-based geoscience studies.